{"title":"Does integrated information theory make testable predictions about the role of silent neurons in consciousness?","authors":"Gary Bartlett","doi":"10.1093/nc/niac015","DOIUrl":null,"url":null,"abstract":"<p><p>Tononi <i>et al</i>. claim that their integrated information theory of consciousness makes testable predictions. This article discusses two of the more startling predictions, which follow from the theory's claim that conscious experiences are generated by inactive as well as active neurons. The first prediction is that a subject's conscious experience at a time can be affected by the disabling of neurons that were already inactive at that time. The second is that even if a subject's entire brain is \"silent,\" meaning that all of its neurons are inactive (but not disabled), the subject can still have a conscious experience. A few authors have noted the implausibility of these predictions-which I call the disabling prediction and the silent brain prediction-but none have considered whether they are testable. In this article, I argue that they are not. In order to make this case, I first try to clarify the distinction between active, inactive (i.e. silent), and inactivated (i.e. disabled) neurons. With this clarification in place, I show that, even putting aside practical difficulties, it is impossible to set up a valid test of either the disabling prediction or the silent brain prediction. The conditions of the tests themselves are conditions under which a response from the subject could not reasonably be interpreted as evidence of consciousness or change in consciousness.</p>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":" ","pages":"niac015"},"PeriodicalIF":4.3000,"publicationDate":"2022-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/28/d3/niac015.PMC9574698.pdf","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/nc/niac015","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 2
Abstract
Tononi et al. claim that their integrated information theory of consciousness makes testable predictions. This article discusses two of the more startling predictions, which follow from the theory's claim that conscious experiences are generated by inactive as well as active neurons. The first prediction is that a subject's conscious experience at a time can be affected by the disabling of neurons that were already inactive at that time. The second is that even if a subject's entire brain is "silent," meaning that all of its neurons are inactive (but not disabled), the subject can still have a conscious experience. A few authors have noted the implausibility of these predictions-which I call the disabling prediction and the silent brain prediction-but none have considered whether they are testable. In this article, I argue that they are not. In order to make this case, I first try to clarify the distinction between active, inactive (i.e. silent), and inactivated (i.e. disabled) neurons. With this clarification in place, I show that, even putting aside practical difficulties, it is impossible to set up a valid test of either the disabling prediction or the silent brain prediction. The conditions of the tests themselves are conditions under which a response from the subject could not reasonably be interpreted as evidence of consciousness or change in consciousness.
期刊介绍:
ACS Applied Electronic Materials is an interdisciplinary journal publishing original research covering all aspects of electronic materials. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials science, engineering, optics, physics, and chemistry into important applications of electronic materials. Sample research topics that span the journal's scope are inorganic, organic, ionic and polymeric materials with properties that include conducting, semiconducting, superconducting, insulating, dielectric, magnetic, optoelectronic, piezoelectric, ferroelectric and thermoelectric.
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